Recombinant Soluble P-Selectin Glycoprotein Ligand-1-Ig Reduces Restenosis Through Inhibition of Platelet-Neutrophil Adhesion After Double Angioplasty in Swine
Bibliographic record
Abstract
BACKGROUND: P-selectin mediates leukocyte recruitment to activated platelets and endothelium through its high-affinity receptor P-selectin glycoprotein ligand-1 (PSGL-1). Platelet and leukocyte activation and binding have been reported after coronary angioplasty and were correlated with restenosis. We investigated the effect of a recombinant soluble PSGL-1 (rPSGL-Ig) on the adhesion of platelets and neutrophils and the development of restenosis after double arterial injury. METHODS AND RESULTS: Four weeks after angioplasty of both carotid arteries in pigs, a second angioplasty was performed at the same sites, 15 minutes after a single administration of vehicle or rPSGL-1 (1 mg/kg IV). Animals were euthanized 1 hour, 4 hours, 1 week, or 4 weeks later. Adhesion of autologous (51)Cr-platelets and (111)In-neutrophils was quantified and histological/morphometric analyses were performed. Although rPSGL-Ig did not affect adherence of these cells 1 hour after injury, it significantly reduced the adhesion of platelets (50% at 4 hours and 85% at 1 week) and neutrophils (50% at 4 hours and 78% at 1 week) to deeply injured arteries. At 4 weeks, the residual lumen was 63% larger in rPSGL-Ig-treated arteries as compared with control arteries (6.1+/-0.6 versus 3.8+/-0.1 mm(2); P:<0.002). The neointimal area was slightly reduced (0.5 in rPSGL-Ig versus 0.7 mm(2) in control). The ratio of the external elastic lamina of injured to uninjured reference segments was >1 in treated arteries and <1 in control arteries. CONCLUSIONS: P-selectin antagonism with rPSGL-Ig inhibits early platelet/leukocyte adhesion on injured arteries and reduces restenosis through a positive impact on vascular remodeling. Hence, rPSGL-Ig may have potential in the prevention of restenosis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".